Cooling Set-point Temperature Research Articles

Definition of a PVT coupled water source heat pump system through optimization of individual components

Exploiting renewable resources considering their discontinuity compared to building needs, necessitates energy system designs that simultaneously maximize generation and storage performance in different seasons. This article presents the optimization of RESHeat European project, concerning a high-performance system which combines water-source heat pump, cooled photovoltaic panels and thermal storage. The research regards the Italian demo site, near Rome, to define a solution for Mediterranean regions which alongside the requirement for heating have notable need for summer cooling. The targets are system's efficiency, with a minimum sCOP of 5, and a minimum 70 % coverage from renewable sources focusing ambient temperature management.A dynamic model of plant and building was used for parametric analysis, which covered separately heating and cooling modes, involving significant parameters: operating temperatures of the heat pump, number of strings comprising the photovoltaic array, volume of the buffer tank connecting PVTs and WSHP and setpoint temperature of a cooler added for tank temperature control in cooling. 184 alternative configurations were evaluated by Multi-Criteria Decision Making (MCDM) method based on energy, economic and logistic criteria, and weighted by five indices. The optimal system includes 15 PVT panels strings for 25 kWp, a 3 m³ storage tank and cooling setpoint temperature of 25 °C.

Cooling collars incorporated with PCM packs and gels to improve indoor thermal comfort in healthy young females

The human neck is one of the most thermally sensitive body regions to nociceptive stimuli. Neck cooling has been extensively researched to improve athletic performance in the heat. However, there has been very little research into the use of conductive neck cooling for indoor thermal comfort. We thereby designed three ultralight cooling collars with cooling gels or phase change materials (GEL6, PCM15, and PCM18). Their cooling performance on thermal comfort enhancement of 14 healthy young female participants under two warm indoor temperatures (28 °C and 30 °C) was investigated. Thermophysiological and perceptual responses, including skin temperature, heart rate, sweating, thermal sensation vote (TSV), thermal comfort vote (TCV), and thermal preference vote (TPV), were extensively studied. Results showed that, in contrast to GEL6, PCM15 and PCM18 significantly decreased the neck skin temperature, with PCM15 exhibiting the greatest reduction of 4.37 °C at 28 °C. PCM15 and PCM18 significantly decreased overall and local TSVs while also increasing overall and local TCVs (all p < 0.05), thus they could maintain >80 % occupant satisfaction at 28 °C. At 30 °C indoor temperature, however, none of these three cooling collars were found to meet the 80 % occupant satisfaction criterion. When compared to GEL6, PCM15 and PCM18 were found to only significantly reduce local TSVs at the head and neck (all p < 0.05). In sum, PCM15 and PCM18 have the potential to increase acceptable HVAC summer cooling setpoint temperature by 2.5 °C, from 25.5 °C to 28.0 °C, leading to a 25 % reduction in building cooling energy consumption.

Sustainable construction of green school building using energy simulation analysis and modeling

The aim of this research is to manage energy efficiency in the design of green school buildings in order to create an optimal educational environment and sustainable architecture. The research method is quantitative and a simulation calculation. For this purpose, Ecotect 2021 software is used for modeling and Revit 2021 and DesignBuilder software for analyzing the results. The case study of this research is the schools built by the School Renovation Organization of East Azarbaijan Province, Tabriz City, based on the cold climate type plan. On this basis, a school designed and implemented by the School Renovation Organization of East Azarbaijan Province was selected based on a non-random purposive sample. The model is implemented in Revit simulation software and the energy analysis is then performed with DesignBuilder software using sustainable materials and renewable energy. The case study building includes appropriate materials in the walls and windows, standard thermal insulation, solar panels on the ceiling and walls, standard ventilation and wind turbines for lighting. The model is analyzed with the DesignBuilder simulator software and then the design is created with the most suitable placement angle based on the optimal energy consumption. The simulation results show that the optimal orientation of the building with the optimal overlap of the shadow finder band and the diagram obtained is 10° to the southeast. The final result of the analysis of the optimal energy consumption of the building at a cooling set point temperature of 24°–26° based on the window to wall ratio from October to February shows a value of 84900 kw/h to 88800 kw/h. According to the optimal design of the building and the results of the energy analysis, the cost of building a school based on the cost of services and infrastructure per gross internal floor area is £959,815, which is the optimal cost of implementing a green school. The results have shown that all selected components in the green schools in the cold regions of Iran to achieve the main goal of using as much solar energy as possible, compensating for unfavorable climatic conditions and creating comfortable conditions for students through the implementation of sustainable architecture.

Energy Performance and Life-Cycle Analysis of Building Retrofits: A Case Study in Abu Dhabi

Highly developed nations worldwide encounter a notable energy demand as their main obstacle. Furthermore, the building sector plays a significant role in contributing to carbon emissions and climate change. In the UAE, buildings consume the largest portion of energy due to the improper selection of design parameters during the building&amp;apos;s design phase, which are specifically tailored for the remarkably hot climate in the country. As a result, various studies, initiatives, and policies are focused on enhancing the energy efficiency of buildings. Additionally, retrofitting existing buildings has emerged as a crucial approach to achieving energy efficiency, resulting in several benefits such as reduced costs for operation and maintenance. This research performed an analysis of a commercial building in Abu Dhabi using DesignBuilder, based on energy modeling and simulation. Five main retrofits were examined, accompanied by a cost analysis to determine the most appropriate retrofit for future investments. The results demonstrate that increasing the cooling set point temperature by 4 degrees led to a 19.53% decrease in the annual cooling load. Additionally, retrofitting the chiller resulted in a 16.11% reduction in the annual cooling load, whereas wall insulation had the least impact as a retrofit. It was observed that improving the chiller&amp;apos;s coefficient of performance (COP) offered significant advantages, with a payback period of around 5 years, making it the most favorable retrofit for investment. However, the glazing and wall insulation retrofits were considered less beneficial due to their high initial costs and long payback periods.

Performance gap analysis for Korean building energy efficiency certification

Performance gap between predicted and measured building energy use can be caused by simplifications and assumptions introduced in the building energy modeling process, uncertainties in building operation such as heating and cooling setpoint temperature, operational hours, occupant behavior, heat generated from lights and equipment, etc. In South Korea, the building energy efficiency certification system (BEEC) evaluates annual energy use intensity (EUI, kWh/m2/yr) and assigns ten certificate levels using ECO2, a EUI calculation tool developed by the Korean government that is based on ISO 52016 and DIN V 18599. Firstly, we collected information on 158 non-residential BEEC-certified buildings and their actual energy usage data. Subsequently, we analyzed the performance gap between predicted and measured EUI for 158 non-residential buildings in terms of building types, heating and cooling degree days, chiller types, gross floor area, window-wall ratio, and envelope U-value. The study reveals that the performance gap is significant, showing mean absolute error ranging from 21.3 to 417.4 kWh/m2/yr, mean biased error from −3.2 to 73.4 %, and the coefficient of variance of the root mean squared error from 57.0 to 304.9 %, respectively. It is also noteworthy that even individual building’s annual consumption during eight years (2014–2021) is annually fluctuating, indicating that even the performance gap is a moving target. This study reassures that building energy certification in the design stage should be understood as a rating, not for a prediction because of many unpredictable and stochastic behavior of building energy systems and occupants.

Sensitivity Assessment of Building Energy Performance Simulations Using MARS Meta-Modeling in Combination with Sobol’ Method

Large discrepancies can occur between building energy performance simulation (BEPS) outputs and reference data. Uncertainty and sensitivity analyses are performed to discover the significant contributions of each input parameter to these discrepancies. Variance-based sensitivity analyses typically require many stochastic simulations, which is computationally demanding (especially in the case of the large number of input parameters involved in the analysis). To overcome these impediments, this study proposes a reliable meta-model-based sensitivity analysis, including validation, Morris’ method, multivariate adaptive regression splines (MARS) meta-modeling, and Sobol’ method, to identify the most influential input parameters on BEPS prediction (annual energy consumption) at the early building design process. A hypothetical building is used to analyze the proposed methodology. Six statistical metrics are applied to verify and quantify the accuracy of the model. It is concluded that the cooling set-point temperature and g-value of the window are the most influential input parameters for the analyzed case study.

Multi-Stage Sensitivity Analysis of the Energy Demand for the Cooling of Grain Warehouses in Cold Regions of China

The early design parameters exert a considerable influence on the cooling energy demand of a granary building in operation. In order to investigate the impact of various parameters on energy use, a grain warehouse energy model was constructed using the Ladybug + Honeybee tools on the Grasshopper platform. Three global energy sensitivity methods were used to analyze the model, and the sizes of the influential parameters were determined and ranked. The study uncovered that the cooling energy demand of the grain warehouse was primarily influenced by factors such as the cooling set-point temperature, roof solar absorptance, roof and exterior wall insulation thickness, window type, and orientation. On this basis, a local sensitivity analysis was conducted for the highly sensitive parameters to identify their influence trend and optimal design range. The results showed that the cooling energy demand of the grain warehouse increases faster as the cooling set-point temperature decreases, with the highest growth rate occurring at a temperature below 18 °C. Lower solar absorptance of the roof is conducive to reducing the cooling energy demand of the grain warehouse. When the thickness of the roof thermal insulation is less than 120 mm and the thickness of the external wall thermal insulation is less than 60 mm, energy use decreases more quickly with greater insulation thickness. It is advisable to use traditional or new windows with thermal insulation and shuttered windows. Furthermore, the optimal position of the long side of the granary was between 10° west and 10° east of north. This research could provide guidance for the energy-saving design and renovation of granary buildings in cold regions of China.

Extending the Thermal Comfort Band in Residential Buildings: A Strategy towards a Less Energy-Intensive Society

Extending set-point temperatures in residential buildings has a significant impact on energy demand and thermal comfort. European governments have adopted this strategy to mitigate the energy crisis. Previous studies attempting to quantify energy savings by extending set-point temperatures were limited due to a lack of building stock characterisation, poor climate representation, and the absence of uniformity in the reference set-point temperature. In this study, a large-scale simulation was conducted, which included six building models covering 90% of southern Europe Köppen–Geiger climates, where 20 °C and 25 °C were the reference heating and cooling set-point temperatures, respectively. This also accounted for the thermal characteristics of the older building stock, built more than 15 years ago, and the new buildings built under the latest version of Directive 2010/31/EU. The results show that reducing the heating set-point temperature by 1 °C can lead to an average demand reduction of 20%, while raising the cooling set-point temperature by 1 °C can lead to a 25% cooling demand reduction. The oldest building stock shows a higher absolute savings potential. Adjusting thermostats by 1 °C in Spanish homes during the winter season could represent a saved natural gas volume of 1.8 million normal cubic meters, nearly 40% of the gas demand of households in 2022. These findings suggest that extending the set-point temperatures in residential buildings can be a promising strategy towards a more energy-efficient society without compromising the occupant’s thermal comfort.

The establishment of design criteria for precision ventilation in open-plan offices

Precision ventilation is used in open-plan offices to establish micro-climate zones according to the metabolic requirements of its occupants. The aim of this study is to determine design criteria and highlight the opportunities and limitations for precision ventilation in large-scale offices. The simulations and experiments were conducted under steady state conditions with fixed airflow from all active chilled beams (ACBs) and constant room temperatures. A temperature difference of 3.5K was maintained between supply and room air in all cases with and without occupants. Results showed that precision ventilation can simultaneously establish low-level (<0.15 m/s), medium-level (<0.45 m/s), and high-level (<0.65 m/s) air velocity zones in the same shared office space such that occupants with different metabolic rates had Predicted Mean Vote (PMV) values maintained within the acceptable limit. The establishment of a single air velocity zone in an open-plan office layout without influencing air velocities of other zones was achieved by lowering the airflow rates of two ACBs by 35%. The vertical and horizontal temperature uniformity was maintained with this precision ventilation system with draught rates of less than 20% for occupants with normal metabolic rates. Comparative analysis using precision ventilation with and without occupants showed that targeted air velocity distribution in the room can be negatively influenced by the absence of any heat sources in any zone. An annual energy saving of up to 15% was achieved by raising the cooling setpoint temperature from 23 °C to 25 °C.

Integrated performance optimization of industrial buildings in relation to thermal comfort and energy consumption: A case study in hot summer and cold winter climate

In the context of environmental protection, researches on thermal performance of buildings represent a growing field, most of which use a variety of linked calculating algorithms to maximize performance metrics. However, previous studies have done little to investigated in balancing energy consumption and indoor thermal comfort of industrial buildings. With various combinations of architecture design parameters, this paper aims to optimize the comprehensive thermal performance of clean plants. Matlab software was used for data preparation, deployment, and sampling. Two thousand simulations based on the different combinations were performed using Monte Carlo technique. The most appropriate combinations of sensitive factors were then analyzed to offer a reference for the architecture design, with the uncertainties of the original alternative parameters being substituted by mathematical statistics and data filtering. The result shows that the total thermal discomfort hours (TTD) increase by 14.95% and the total energy consumption (TEC) increases by 35.19% when the heating setpoint temperature is raised from 14 °C to 24 °C. The TTD increase by 3.93% and the TEC decreases by 21.68% when the cooling setpoint temperature is raised from 20 °C to 28 °C, respectively. The findings can contribute to understanding of the parameter combinations enhancing the comprehensive thermal performance of industrial buildings.

Real-time model predictive cooling control for an HVAC system in a factory building

This paper presents the results of model predictive control (MPC) using multiple deep neural network (DNN) models for the cooling system of a factory building. The target building accommodates a large space (80 m × 60 m × 9.7 m) and serves cooling via 45 diffusers connected to a direct expansion air handling unit that comprises two air supply fans and four condensing units. The authors developed 10 simulation models using a DNN: One predicts the supply air temperature of the HVAC system, while the others predict the indoor temperature of nine zones. The models can sufficiently predict the thermal behavior of the HVAC system (normalized mean bias error (NMBE): −1.2 %, coefficient of variation of the root mean square error (CVRMSE): 3.8 %) and indoor environment (NMBE: 1.1 %, CVRMSE: 1.3 %). The purpose of the MPC is to minimize the energy consumption of the condensing units while maintaining the cooling set-point temperature. The MPC was applied to the target building for a sampling time of 10 min, for four weeks, from August 23 to September 17, 2021. It was found that energy consumption decreased by 35.1 % compared with the baseline period, while satisfying the cooling set-point temperature maintenance condition. Finally, the authors highlight that the DNN-based MPC is a practical approach sufficient for predicting indoor thermal behavior and has significant potential for energy saving.

Odor from Building Air Conditioners: Emission Characteristics, Odor Compounds and Influencing Factors

The odor generated by air conditioners is an important factor influencing the perceived air quality in buildings. In this study, different types of air conditioners and air filters were investigated to study the level of odor emission related to the operation state of the compressor, to identify the odor compounds and to analyze the cooling setpoint temperature on emitted odor intensity. Results show that the odor from constant frequency air conditioner use is periodic and stronger than that from variable frequency air conditioner use due to the different operation strategies of the compressor, which affect the evaporation of condensed water on the surface of the cooling coil. Ethyl acetate, acetic acid, 2-ethyl-1-hexanol, acetaldehyde, hexanal, nonanal, toluene and n-hexane are identified as odor compounds by Odor Active Value (OAV), Gas Chromatography/Olfactory/Mass Spectrometry (GC/O/MS) and Flavornet methods. The higher cooling setpoint temperature would lead to stronger odor, due to greater release of hydrophilic odorous compounds from condensed water. In our opinion, reducing the residual condensed water in air conditioners may be the key to control odor emission before purification.

Is 24.9 °C Too Hot to Think? A Call to Raise Temperature Setpoints in Australian Offices

The current +−0.5 PMV (Predicted Mean Vote) targets adopted by NABERS (National Australian Built Environment Rating System) is the practical range deemed acceptable for 90% acceptability for commercial buildings in Australia, however thermal comfort satisfaction scores measured in office buildings still show high percentages of dissatisfied occupants. This paper aims to demonstrate the potential of curbing energy consumption from commercial buildings in Australia by increasing summer temperature set-points. A 10-year NABERS dataset, along with objective and subjective thermal comfort and air quality data from NABERS-certified offices are investigated in this study. Furthermore, different simulation scenarios are tested to investigate the discomfort hours and energy consumption for various summer temperature setpoints. Result analysis shows that occupants’ satisfaction in NABERS-certified buildings was not within the 90% satisfaction, with being too cold/hot as the main source of dissatisfaction. Objective measurements also showed temperature was out of recommended range for several datapoints. Simulation results indicate that, within the average range of 21–24.9 °C, there is not a significant difference in discomfort hours that could drive the selection of one temperature set-point over the other. Challenging the current practices, results suggest that a cooling set point temperature on the upper limit of the range indicated by the Australian standard AS 1837–1976 may minimize the energy consumption without significantly increasing discomfort, or even increasing the perceived satisfaction with the indoor environment.

Quantifying CO2 Emissions and Energy Production from Power Plants to Run HVAC Systems in ASHRAE-Based Buildings

Recent evidence available in the literature has highlighted that the high-energy consumption rate associated with air conditioning leads to the undesired “overcooling” condition in arid-climate regions. To this end, this study quantified the effects of increasing the cooling setpoint temperature on reducing energy consumption and CO2 emissions to mitigate overcooling. DesignBuilder software was used to simulate the performance of a generic building operating under the currently adopted ASHRAE HVAC criteria. It was found that increasing the cooling setpoint temperature by 1 °C will increase the operative temperature by approximately 0.25 °C and reduce the annual cooling electricity consumption required for each 1 m2 of an occupied area by approximately 8 kWh/year. This accounts for a reduction of 8% in cooling energy consumption compared to the ASHRAE cooling setpoint (i.e., t_s = 26 °C) and a reduction in the annual CO2 emission rate to roughly 4.8 kg/m2 °C. The largest reduction in cooling energy consumption and CO2 emissions was found to occur in October, with reduced rates of approximately–1.3 kWh/m2 °C and −0.8 kg/m2 °C, respectively.

Deciphering optimal mixed-mode ventilation in the tropics using reinforcement learning with explainable artificial intelligence

The application of mixed-mode ventilation (MMV) in the tropics is challenging, given its hot and humid climate. Consequently, there are limited periods when operating in natural ventilation (NV) is desirable. Furthermore, the potential to use NV diminishes at locations characterized by generally light winds. Given the complex interactions in MMV, this study aims to use reinforcement learning (RL) to identify relationships that can further reduce cooling energy use while maintaining occupant thermal comfort. The control variable variables considered include the percentage of window opening area and dynamic cooling setpoint temperature. Results show that RL can achieve a 52% reduction in cooling energy while maintaining good thermal comfort and indoor air quality compared to the existing baselines that typically involve switching between NV and air-conditioning based on outdoor conditions. We then developed an Explainable AI (XAI) framework to prompt building scientists toward new insights into MMV control in the tropics, which consists of shapley additive explanations (SHAP) and decision tree. The SHAP is able to improve the transparency of RL strategy by revealing the impact of each input on the final decision and the decision tree can extract the key control rules from RL. Using the XAI framework, this study also identified that the RL algorithm was taking advantage of the internal thermal mass to increase cooling efficiency. The extracted rules are further applied to the actual testbed, showing the feasibility of the rules extracted by XAI approach.

Thermal adaptation of different set point temperature modes and energy saving potential in split air-conditioned office buildings during summer

The Chinese government issued a regulation that the cooling set point temperature (SPT) in office buildings cannot be lower than 26 °C. Therefore, SPTs were divided into different modes: SPT≥26 °C and SPT<26 °C. To study the human thermal adaptation of different SPT modes and determine the comfort and energy saving of the policy, a field test and subjective questionnaires were conducted in 21 split air-conditioned (SAC) office buildings during the warm season in the cold zone of China. We measured the environmental parameters and subjects' skin temperatures, and the subjective thermal responses were also investigated. The results showed that 45% of the air conditioner SPTs were less than 26 °C. In the high SPT mode, people's physiological adaptability to the warm environment was stronger, and subjects were more active in reducing clothes and increasing air velocity to improve thermal discomfort. Because the two modes had similar thermal histories and the same perceptual control, in the same SET ranges, no significant differences were found in thermal sensation, acceptability and comfort between the two SPT modes. The effects of long-term indoor thermal history on human thermal adaptation varied with the thermal exposure type, mode and intensity. From the analysis of thermal adaptation, the rationality of the policy was fully proved, and it was determined that SAC office buildings could save 26.4–35.2% of power energy consumption by reasonably increasing SPT in the cold zone. The results can enrich the thermal adaptation theory and provide a theoretical basis for the government's energy-saving policies in SAC office buildings.

Indoor Thermal Environment and Energy Characteristics with Varying Cooling System Capacity and Restart Time

Office cooling systems are controlled with on/off control according to typical occupancy patterns. During unoccupancy, the cooling systems remain switched off to reduce unnecessary energy consumption. During occupancy, however, the cooling systems are in operation to decrease the indoor air temperature, which is increased during unoccupancy, to the cooling set-point temperature. The time required to decrease the indoor air temperature to the cooling set-point temperature is defined as the “recovery time”. According to the recovery time, the indoor thermal comfort at the occupancy start time may worsen, and unnecessary energy may be consumed. Moreover, a cooling system capacity affects the recovery time and the energy consumption because the amount of heat that the cooling system can remove varies according to its size. Therefore, it is necessary to analyze the indoor thermal environment and the energy consumption according to the capacity and the restart time of the cooling system. This study implemented a building system energy simulation using EnergyPlus to evaluate the indoor air temperature, recovery time, and energy consumption of the cooling system while varying the capacity and restart time. As a result, the recovery time was between 49 and 425 min. and energy consumption varied between 419.0 and 521.4 kWh for various capacities. The recovery time was between 26 and 153 min. and energy consumption was between 426.0 and 439.0 kWh for various restart times.

Investigating Optimum Cooling Set Point Temperature and Air Velocity for Thermal Comfort and Energy Conservation in Mixed-Mode Buildings in India

In warm and hot climates, ceiling fans and/or air conditioners (ACs) are used to maintain thermal comfort. Ceiling fans provide air movement near the skin, which enhances the evaporation of sweat, reduces heat stress, and enhances thermal comfort. This is also called the cooling effect. However, AC usage behaviour and the effects of elevated air speed through the use of ceiling fans on indoor operative temperature during AC usage are not widely studied. This study investigated the optimum AC (cooling) set point temperature and air velocity necessary for maintaining thermal comfort while achieving energy conservation, in mixed-mode buildings in India, through field studies by using used custom-built Internet of Things (IOT) devices. In the current study, the results indicate a 79% probability that comfort conditions can be maintained by achieving a temperature drop of 3K. If this drop can be achieved, as much as possible, through passive measures, the duration of AC operation and its energy consumption are reduced, at least by 67.5 and 58.4%, respectively. During the air-conditioned period, there is a possibility that the cooing effect is reduced because of increase in operative temperature due to ceiling fan operation. Therefore, the optimum solution is to maintain the highest AC set point and minimum fan speed setting that are acceptable.

Effect of Architectural Building Design Parameters on Thermal Comfort and Energy Consumption in Higher Education Buildings

It has been challenging for designers to identify the appropriate design parameters that would reduce building energy consumption while achieving thermal comfort for building occupants. This study aims to determine the most important architectural building design parameters (ABDPs) that can increase thermal comfort and reduce energy use in educational buildings. The effect of 15 ABDPs in an Australian educational lecture theatre and their variabilities on energy consumption and students’ thermal comfort for each parameter were analysed using Monte Carlo (MC) techniques. Two thousand simulations for every input parameter were performed based on the selected distribution using the Latin hypercube sampling (LHS) technique. Sensitivity analyses (SA) and uncertainty analyses (UA) were used to assess the most important ABDPs in terms of thermal discomfort hours and energy consumption. The study found that the ABDPs, such as cooling set-point temperatures and roof construction, significantly reduce the operative temperature by up to 14.2% and 20.0%, respectively. Consequently, these reductions could significantly shorten the thermal discomfort hours, thereby reducing energy consumption by 43.7% and 41.0%, respectively. The findings of this study enable building designers to identify which ABDPs have a substantial impact on thermal comfort and energy consumption.

스마트팜 적용 피복재의 시험을 통한 성능평가 및 냉방부하 분석

The thermal performance database of the covering material which can be used as input data for the smart farm cooling load simulation performance evaluation was analyzed through the test evaluation. Methods: The solar heat gain coefficient of the covering materials (PE, PMMA, PC double layer, woven film) was compared and analyzed through the Korean standard test method and input data was derived. Based on the thermal input data, the cooling load simulation of smart farm was conducted and the simulation performance evaluation of each case was performed to analyze how the indoor cooling load changes by covering materials. Results: The cooling load of the PC double layer was the lowest at 424 W/㎡, and the PE film was the highest at 559 W/㎡. The coefficient of heat transmission was 3.7 W/㎡ ·K~6.7 W/㎡ ·K for each covering materials, and the solar heat gain coefficient was evaluated as 54%~90% visible transmittance was 50%~88%. The cooling load of the PC double layer and PE film showed a difference of 135 W/m2(24%), indicating that the selection of the coating material greatly affects the cooling load. The cooling load was reduced by 25.3% when the cooling setpoint temperature was controlled, and the cooling load was reduced by 35.8% when the internal shading rate was applied by 60%.